Although the presentation is titled Connected Knowledge, Collective Learning, Allison talks more about collective knowledge (which she defines as the knowledge distributed across people, machines, networks and artefacts) and Collective learning (the term used to describe learning processes that make use of this collective knowledge).

Collective Knowledge is then, the output of charting – connecting, consuming, creating and contributing by people. In her opinion, the individual and the network are indivisible and collective learning itself is emergent. Also, the individual views the networks, groups and collectives through the lens of her own goals.

Allison defines groups as composed of the individual, team, manager and colleague with similar skills. Network is broadly defined to include this group and external contacts, peers with similar goals and anyone.

The quest is to understand the inter-relationships inherent in groups and networks, understand the forces that bind individuals in their learning, understand the learning process, how collective learning can help improve outcomes at the workplace and the literacies required to achieve collective learning and how to understand how different resource types might support collective learning and knowledge building.

Collective knowledge is defined as formal learning, libraries, dynamic knowledge (wikis), collaborative spaces, knowledge networks, smart information, your knowledge, shared and recommended resources. The Collective is defined as a combination of groups, networks and collective knowledge. The individual is as the center and connects with groups and networks, creates/consumes/contributes to collective knowledge. Goals may change/evolve over time and so may paths, Allison feels, and this where she says charting really helps.

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In an earlier post, I had visited collaboration techniques and some concepts there that I had encountered and thought about. One conclusion was that:

It goes back to us, as individuals, and how we collaborate as subjects, alone or in teams or in networks. If the capability to collaborate in structured ways is learnt and becomes “native” so will adoption on a more widespread basis.

How can collaboration or the capability thereof, go native? By imparting a purpose to collaboration, I am focusing on collaboration that needs to be explicit, rather than implicit (or as a function of collectives). How can it become an essential part of our daily workflows?

One obvious component is technology of some sort – phone, Internet-based etc. and the knowledge & skills on the technology that you need to collaborate.

The other obvious component is your network and the level of access that you have to people with whom you can collaborate.

The third component is the collaboration skill itself, which is composed of not only soft skills (including social etiquette and cultural sensitivity), but also language skills (how effectively can you communicate) and knowledge of various structured and unstructured collaboration techniques (for example, collaboration could also include negotiation or mediation apart from the regular terms in which we view collaboration).

The fourth component is the content/domain of collaboration. Techniques like the Johari window are pretty useful here to analyze the domain with respect to the collaboration participants and their level of knowledge.

An important fifth dimension, apart from technology, networks and collaboration skill, also emerges – context. It is really important to understand state of the world before, during and after the collaboration process ends. If we are able to capture that, then we are able to do two things – one, document the process for others to learn from and two, measure the outcomes and build performance indicators.

At this time (or at any time in the past), these have always existed in some form or the other. Online/digital technology scores because of its capability to bring diverse geographically distributed people together on a collaborative platform, but leaves much to be desired in terms of facilitating the use of formal techniques for collaboration.

In our experience, we have more or less learnt to collaborate by experience (I would say this would be a fairly acceptable generalization) and by making mistakes. But also a lot by how we see our peers and seniors collaborate. We take these complex skills involving social interaction, emotional control, tact, courtesy and so many other dimensions to produce the results we so desire. There are also a large number of successful models that people have developed over the years. In fact Stephen Covey’s Sixth Habit is Principles of Creative Cooperation.

It is so difficult for formal models to be built in a highly subjective and individualized area. I quote Yes Minister where Hacker reveals the three varieties of Civil Service silence – Discreet, Stubborn and Courageous silence.

… He also warned me of the ‘Three Varieties of Civil Service Silence’, which would be Humphrey’s last resort if completely cornered: 1 The silence when they do not want to tell you the facts: Discreet Silence. 2 The silence when they do not intend to take any action: Stubborn Silence. 3 The silence when you catch them out and they haven’t a leg to stand on. They imply that they could vindicate themselves completely if only they were free to tell all, but they are too honourable to do so: Courageous Silence. (The Complete Yes Minister, pp. 93-4)

How does one depict or infer Courageous Silence online on a Chat or Social network discussion?

However, there is value that exists if we do use/adapt somebody’s well thought out or experimented mechanism or recipe for collaboration. After all that is where a lot of people make money in training because they can interpret and adapt to the individual’s context when suggesting a recipe or building capability on a specific technique.

To really be useful and pervasive, we must find ways to enable these dimensions on an Internet scale, in our applications. We must make these tools & techniques and the knowledge thereof easy to grasp and implement. And this process will continue to evolve and benefit from multiple related developments in technology and technique.

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While researching structured collaboration techniques, I came across some interesting work people are doing. Mindquarry, for example, provides a model of collaboration patterns based on 4 elements – people, productivity software, collaborative software and methods. I had earlier referred to Mindtools, who provide a rich set of structured collaboration techniques, like for example starbusting, which is a form of brainstorming. Also, Value based management offers a host of techniques, models and theories.

Essentially, structured technology aided collaboration techniques are a medium through which learning efficiencies can be increased. These techniques:

are contextual to domain

are contextual to collaboration type (say, brainstorming vs voting)

are open or close ended (in terms of time, scope, boundaries etc)

could be ad-hoc or planned

are quantifiable (both quantitatively and qualitatively speaking)

are historically referenceable (audit trails for recorded collaborations)

have rules of engagement

can be structured to the desired level (sequence of activities, organization of inputs, permissions and access roles)

are sensitive to scale of audience, available knowledge and other physical parameters

We present a model of collaboration patterns as reusable conceptual structures capturing essential collaboration requirements. These patterns include goal patterns (what is the collaboration about?), communication patterns (how does communication to accomplish goals take place?), information patterns (what content knowledge is essential to satisfy collaborative and communicative goals?), task patterns (what particular information patterns are needed for particular action or interaction goals?), and meta-patterns (what patterns are necessary to interpret, link and assess the quality of the other collaboration patterns?). We show how these patterns can be used to activate communities of practice by improving their collective, distributed memory of communicative interactions and information. We outline an approach that structures how collaboration patterns in communities of practice can be elicited, represented, analyzed, and applied. By presenting a realistic scenario, we illustrate how community memory could be activated in practice.

The other key component is to understand what is the need to collaborate and the forces impeding the required collaboration. This is key to understanding whether collaboration techniques shall be used, substituted by informal methods or not used at all. It is important to understand if they are “over sold and under used” or are “methods seeking an application” or are really cost-effective or intuitive. We have seen that in software engineering too and this may require change management to implement in enterprises.

In other words, the challenge is not quite really all about the technology or process, but is perhaps more about the individual mindset and the overall objectives with which structured collaboration techniques are to be implemented (basically saying that a great process or tool does not automatically ensure collaboration that follows the process or uses the tool or format).

It goes back to us, as individuals, and how we collaborate as subjects, alone or in teams or in networks. If the capability to collaborate in structured ways is learnt and becomes “native” so will adoption on a more widespread basis. On the other hand, organizations or learning delivery modalities can include, as mandatory components, such patterns, tools or processes as part of the workflow.

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Janet Clarey sparked off some serious thinking in my head about, really, what we are measuring in terms of RoI on training initiatives. The post in question was Rob Wilkins’ Why do we sacrifice? and you can find our conversation in the comments (and hopefully contribute your thoughts too!). George raises some relevant ideas too in his post On the value of assessments.

I am really intrigued. How can we create metrics (and data collection parameters) so that we can derive RoI from the activities in a learning network?

Almost directly related is the question of how LMS providers, as reviewed in Janet’s series LMSs that kick ass, can contribute to this activity. Outstart believes the LMS and the Social Network are separate platforms, the former controls, tracks and reports on formal training initiatives while the latter enable rather than control informal learning. As Janet reports, Jeff Whitney from Outstart comments:

We developed our social media platform separate from our LMS as many informal learning initiatives do not require the formal reporting and tracking features of an LMS. But we also integrated the solution with our LMS to support activities like the invaluable, ad hoc student-to-student and student-to-instructor knowledge sharing that surround formal learning initiatives.

Incorporating multiple modalities of learning is not the challenging part. We can build communities of practice into business workflows and develop social media environments. The challenges, in Cornerstone’s view, revolve around engagement and tracking. Getting people to contribute and then assessing the value of this 80% social learning element for the organization.

Gen21’s product focus is on its core product functionality. To that end, core collaborative features in the LMS cover the key aspects of social media – collaborative authoring, wiki’s, messaging, message boards, interactive web environments, content rating, library, etc. Imaginative use of these functions achieves a reasonable level of “social” interaction

…….For Gen21, social media is simply another analogous function that clients may choose to use in their learning toolkit. The elements of social media in our LMS are those that related most directly to our mission to enable learning.

Alternately, for companies ready to move beyond a course- and LMS-centric view of social learning, Mzinga can provide a Community strategy where social networking and social media are more prominently featured and formal learning elements take on supporting roles. In this model, Mzinga “hides” the LMS, but still exposes certifications, compliance, curriculum, virtual classroom, and courses through deep, direct links. (emphasis added)

There are others that Janet talked with such as ElementK and Meridian that are interesting reads. It seems to be clear that LMS providers have integrated social media functions to a large degree, in one way or the other. And that some seem to have some tracking and reporting linkages as well, though I don’t know to what level of detail or with what specific approach in mind.

Would love to hear from the community what they feel!

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I am investigating the connections between Informal Learning, Communities of Practice, Network of Practice and Connectivism. Found an interesting conversation between Jay Cross, George Siemens, Dave Cormier and (on chat) Stephen Downes on EdTechTalk#23, Nov 3, 2005.

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What inherently constitutes a connectivist learning ecology? What specifically differentiates it from a collaborative, Web 2.0 or informal learning enabled learning environment? Was the CCK08 course representative of the Connectivist learning ecology?

I like the idea of thinning our classroom walls and allowing connections to be formed between concepts from other subject areas. But that responsibility shouldn’t rest on the educator. “Getting on the same page” (author’s words) seems a bit at odds with opening up class rooms. We need to all get on our own page, form our own connections, our own understanding of different fields. It seems that the desire still runs high for educators to apply increased organization when problems become intractable. What is really needed is a complete letting go of our organization schemes and open concepts up to the self/participatory/chaotic sensemaking processes that flourish in online environments.

The idea of connectivism (Drexler, 2008 ) ties in well with social constructivism, demonstrating how new generation learners use the power of our networked world to tap into remote sources of knowledge, including experts in various fields. These learners work in a world without boundaries from a technological point of view. They are adept at finding, storing, managing and sharing information using new web-based applications. More importantly, they are involved in knowledge creation, using blogs, wikis and other on-line applications to mash and developing new ways of looking at and using information. These students bring fresh challenges for learning institutions across the educational spectrum, given their need for a fast moving, game oriented learning (Pensky, 2001) which traditional learning environments are hard pressed to provide.

But I want to discuss the difference between the creation of an ecological blueprint (if there could be one) that “allows” connective learning and what would constitute an ecological blueprint that “is” inherently a connective learning design/blueprint. For example, the difference between saying “the hotel lounge is Wifi-enabled” is different than saying that “I can check my email in the hotel lounge”. After all, it’s the conversation rather than the blogging tool that’s more important, right?

George Siemens contrasts behaviourism, cognitivism, constructivism and connectivism in the light of Ertmer’s and Newby’s five definitive questions to distinguish different learning theories. For connectivism, he states:

How does learning occur? – Distributed within a network, social, technologically enhanced, recognizing and interpreting patterns

What is the role of memory? – Adaptive patterns, representative of current state, existing in networks

How does transfer occur? – Connecting to (adding) nodes

What types of learning are best explained by this theory? – Complex learning, rapid changing core, diverse knowledge sources.

(George’s responses in italics)

George and Stephen also talk of the impact of chaos theory, self organization and complexity on the learning process. They also refer to the impact of this way of learning on traditional notions of power, control, validity and authority (among others). So what would constitute the learning ecology that is connective? It should be one that inherently:

Enables us to recognize and interpret patterns that exist (way finding, sense making) ; indeed, generate our own new patterns

Helps us build adaptively on and capture existing patterns given a rapid changing core and diverse knowledge sources

Provides a distributed environment (both for knowledge and people)

Provides avenues for social collaboration

Is technologically enhanced to deal with diverse processes/circumstances such as negotiating information overload, self organization, determining order within chaos etc.

Enables us to leverage and expand on a network that is diverse

Helps us build ties at varying strengths that in turn may determine the efficacy/effectiveness of our learning

Enables us to negotiate complex learning needs

Replace “what would constitute a connective learning ecology?” with “what kind of educator would suit or engender a connective learning ecology?” and it becomes easier to think about the problem instantly.

That is, the answer that the educator should “model” and “demonstrate” his connective learning process/ability/efficiency while the learner should “practice” and “reflect” (I think “observation” and “experimentation” are equally critical skills), makes sense because the ability to do all of the above needs to be learnt by the learner. The objective is perhaps that the learner be empowered with the learning skills and ecologies of the educator (as George Siemens says “…A curator is an expert learner”).

What if there was no educator or formal role for one? What happens in that truly open, autonomous, distributed, uncontrolled network? Is there an ecology for the solitary learner; for the ones that are faced with unequal access; those who have technological/social barriers or limitations?

In a sense then, perhaps we should look at the design and metrics of a connectivist ecology from a different lens altogether – where the ecology contains components that inherently propel the learner to become a curator.

Instead of providing a chat tool and a structured interaction and participation schedule, it should provide (for lack of a better technologically unchallenged term) a “default” mechanism for learning that propels the learner to make connections, practice and reflect, observe & build & recognize distributed knowledge patterns.

It is here that the discussion around types of networks becomes really important. At the neural level, it is really immersion into the environment (“increased awareness?”); at the conceptual level it is the ability for the ecology to provide some ways of exploring and building concept patterns and at the social level, the learning network of people (and devices) itself in a given context. It is here also that we should perhaps attack the concerns around motivation and participation.

Perhaps when the three (and there may be more) types of networks come together in some way, they become really powerful for learning. For example, experiencing rain-drops, recognizing the dark cloud visual and listening to the thunderclap, associating it with concepts of cloud formation and effects of rainfall, and, warning your friend not to venture out, may be an example of learning could manifest itself given this three way association (there could be self spiraling associations within a network type itself).

Where would the metrics then come in and how would they be designed? In another corporate context, I once read a powerful article by John R. Hauser and Gerald M. Katz titled “Metrics: You are what you measure!”. In my mind and as they state, successful metrics are good if the actions and decisions which improve the metrics also improve the firm’s (read “learner’s”) desired long term outcomes (read “learning ability” or “expertise”). They list seven pitfalls of metric design and how these can completely subvert the metric design exercise. They also list an equal number of steps to design good metrics such as “Listen to the customer” and “Understand the inter-relationships” all of which I think are useful ways to think about what to avoid and what to follow.

The main point is that we need to understand if score, time elapsed, distance between two nodes (a.k.a. social network analysis), e-portfolio submission & ratings et al are good metrics in this connectivist ecology. Instead, wouldn’t we ask questions relating to or perform investigation into how well the learner is able to learn using the “default” mechanism I referred to earlier? For example, speed of learning could be perhaps (or maybe I am being too simplistic) the rate of change of new patterns, network connections, conversations; or the measure of expertise would be the number, qualitative rating, network perception or rate of interaction between you and the resources in your network?

As always, would love to be corrected and to know your thoughts!

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I have an occasion to do a little research on the Montessori method. Named after Dr. Maria Montessori, who, in 1896, was the first woman in Italy to graduate out of medical school, the Montessori method seems to have rich similarities with Connectivism.

The basic Montessori concepts are pretty well known by now (Montessori in Perspective, 1966). 1 – The teacher must pay attention to the child, rather than the child paying attention to the teacher. 2 – The child proceeds at his own pace in an environment controlled to provide means of learning. 3 – Imaginative teaching materials are the heart of the process. 4 – Each of them is self-correcting, thus enabling the child to proceed at his own pace and see his own mistakes. If you were to look inside a Montessori classroom, you would get the impression of “controlled chaos” because each child would be quietly working at his private encounter with whatever learning task he or she chose (Montessori in Perspective, 1966).

Dr. Montessori said “I studied my children, and they taught me how to teach them.” And also her general principle – “first education of the senses, then education of the intellect”.

‘The essential thing is for the task to arouse such an interest that it engages the child’s whole personality’ (Maria Montessori – The Absorbent Mind: 206).

This connected with a further element in the Montessori programme – decentring the teacher. The teacher was the ‘keeper’ of the environment. While children got on with their activities the task was to observe and to intervene from the periphery. (Here there are a number of parallels with Dewey).

The Microlearning conference 2005 proceedings“Learning and Working in New Media Environments” (June 23-24, 2005, University of Innsbruck, Austria) has an interesting paper by Gernot Tscherteu titled “The Blogosphere Map – Visualizing Microcontent Dissemination” (looks very similar to what Valdis Krebs does :)). The principles of the Montessori method are referenced in the context of microlearning:

the Montessori pedagogue is acting in the background, and,

Learning by playing in mixed groups

Free schedules, no collective teaching

Prepared environment

Learning materials are kind of small interactive games for real life learning experiences

Sensomotoric

Very similar to what I have learnt about connectivism e.g. the second is a characteristic of networks if you think about it.

Microlearning itself seems to be an interesting concept. Theo Hug summaries different dimensions together in his paper “Microlearning: A New Pedagogical Challenge” in the same Austrian conference.

There is not one precise definition which covers all the different concepts. In my view there are versions which are brought forth by different interpretations of particular dimensions such as:

Time: relatively short effort, operating expense, degree of time consumption, measurable time, subjective time, etc.

Content: small or very small units, narrow topics, rather simplex issues, etc.

Curriculum: part of curricular setting, parts of modules, elements of informal learning, etc.

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Is there something like that at all? In a discussion yesterday, an important point was made by a participant – we don’t want perfect environments to be created for our learners, even if we could create them.

Why is this important to discuss? Everywhere around us there are “frictional” forces that impede or obscure – could be authority, access, lack of infrastructure or others – the learning process.

The ability to learn to cope with these forces becomes equally critical as the process of sense-making or wayfinding in a connectivist paradigm.

What is this ability? The best way to place this ability in stark contrast is to assume a limiting factor. Let us say the individual has no access to (say) Web 2.0 technology. Specifically, the ability to form online networks / inter-personal relationships and instant online collaboration does not exist for this individual.

For her, sense-making would be based in a world of books & letters, local resources, chance encounters and possibly luck in tems of finding the right connections for her purpose. She would then possibly compensate for this frictional force in many other ways and an important factor here would be individual agency, apart from environmental facilitation and personal skill. She would actively seek and pursue opportunities that allow her to overcome this frictional force in a unique manner.

This ability to innovate & learn within physical world and personal constraints is equally important as the process of learning itself – maybe an inseparable aspect.

Connectivism makes the negotiation of information an important aspect of the learning ability, maybe it should include negotiation of real world constraints as well.

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In a previous post, I tried to identify some of the impacts of connectivist practice on visual design. Primarily, these are:

Usability

Visual “languages”

HCI Design

Programmable patterns depicted visually

Shared visual patterns

Ease of authoring new media and media mashups

I was referred to ManyEyes through a blog post (I think it was George’s post) and found it extremely interesting, not because of what it does (because that has been experimented earlier), but because of the way they have put it together – large number of visualization types and ease of authoring.

What is especially interesting is what they call topic hubs. What this means is that anyone can go in, start a discussion topic and add visualizations and data to it.

So these are really combinations of two different ideas – mashup between data and presentation style, and, collaboration around a shared object(s).

I think these are powerful ways of visual collaboration. Within connectivism, they offer an important way of making connections thereby impacting learning.

What would be even more interesting is if someone took two or more different media mashups and started mashing them together.

For example, a world map showing pollution levels across major cities could be drilled down (or linked to other related visualizations) into a bar chart which could then be tagged to a Technorati tag list in addition to a Twitter conversation in addition to….

For the visual designer (as well as the educator), these represent important starting points to think about the multi-dimensionality provided by connectivism.

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Outliers, Gladwell’s 2008 book (and I have not read his earlier work yet), is something that I started on yesterday. It has caught my attention from page one. Gladwell wants us to

…appreciate the idea that values of the world we inhabit and the people we surround ourselves with have a profound effect on who we are.

Gladwell explores success (“Why do some people achieve so much more than others? Can they lie so far outside the ordinary? What is the secret of their success?”). These questions directly attack our notions of talent and expertise. And in many ways bring out the effect systemic decisions may have on development of this talent and expertise – somewhat chaotic, sensitive to initial conditions.

In his chapter on the “Matthew Effect” (Matthew 25:29; term coined by sociologist Robert Merton), Gladwell does an interesting analysis. He took the birth months of junior hockey league players in Canada and found that most of them were born between the first three months of the year. Having found this, he went on to study other such teams, the US non-school Baseball league, European soccer, the Czech National Junior soccer team and the studies by economists Kelly Bedard and Elizabeth Dhuey on the relationships between TIMSS (Trends in International Mathematics and Science Studies) scores and birth month. He found similar patterns in the data!

Why? Apparently because, each of these had a system defined cut-off date for eligibility. In the Canadian Junior Hockey leagues, the cut-off date is January 1. So a player reaching the age of 10 on Jan 2, could be playing alongside someone who would reach that age perhaps in December that year – a huge difference at the age of 10, would you say?

Similarly, in TIMSS, among the fourth graders, the children who were the oldest scored at least 4-12 percentile points better than the younger children!

So practically speaking, if you group by “ability” and put older (“more mature”) students in advanced streams where they are given better opportunities to learn, they then have an advantage that is iteratively increased as they move from grade to grade.

Huh! Dubner and Levitt (Freakonomics) would be pretty kicked to see this research 🙂 .

The other aspect is that the kids who were born in the later months got lesser and lesser attention or opportunity (very few Czech soccer players born between July-December, for example), which meant that a large population of students did not make it because of when they were born?

So what does it mean to have innate talent or intelligence then? What it does it mean to be an expert? Gladwell quotes neurologist Daniel Levitin who states:

The emerging picture from these studies is that ten thousand hours of practice is required to achieve the level of mastery associated with being a world-class expert – in anything. In study after study, of composers, basketball players, fiction writers, Ice skaters, concert pianists, chess players, master criminals, and what have you, this number comes up again and again. Ten thousand hours is equivalent to roughly three hours a day, or twenty hours a week, of practice over ten years. Of course, this doesn’t address why some people don’t seem to get anywhere when they practice, and why some people get more out of their practice sessions than others. but no one has yet found a case in which true world-class expertise was accomplished in less time. It seems that it takes the brain this long to assimilate all that it needs to know and achieve true mastery.

That’s interesting because, where do you get the opportunity (and where is it systematically denied?) to practice twenty hours a week over 10 years if the analysis is true at all.

Gladwell goes on to look at Bill Joy, the Beatles, Bill Gates and many more. The refrain is that opportunity to succeed is too important a factor to consider in your success. And that, intuitively, strikes more than a single chord in me personally and because of what I have experienced in CCK08.

Open, accessible networks may provide our children what they need to be successful. Their ability to form connections and uncover opportunities for individual learning and growth may result in covering some of the great disparities caused by existing world structures, be they economic, educational, legal or others.